GridStix: Supporting Flood Prediction using Embedded Hardware and Next Generation Grid Middleware

Hughes, Danny; Greenwood, Philip; Coulson, Geoff; Blair, Gordon S.

doi:10.1109/wowmom.2006.49

Cited by 44 publications

(33 citation statements)

References 7 publications

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“…Some of them have been implemented, but only a few have been deployed [2], [3], [5], [8], [7], [14], [28], [30]. Common to all deployments is their specificity to the tackled application and the steep learning curve the developers took towards deployment.…”

Section: Related Workmentioning

confidence: 99%

FieldMAP: A Spatiotemporal Field Monitoring Application Prototyping Framework

et al. 2009

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Abstract-The fundamental aim of monitoring is to identify abnormalities in the observed phenomena and allow inference of the likely cause. Faced with the common problems of spatially irregular sensor distribution and intermittent sensor measurement availability, key to fulfilling the monitoring aim is filling in the spatio-temporal gaps in the data. Whilst Wireless Sensor Networks (WSN) technology, combined with MEMS availability potentially offer sensing solutions for a variety of application domains, in the context of monitoring applications a conceptual shift is needed from currently available, point-measurement based "sense-and-send" systems towards the provision of phenomena field representations, in real-time, enabling effective visualisation of the spatio-temporal patterns.This paper argues the case for a generic, rapid prototyping framework for end-to-end sensing systems that support the approach of providing field representations for visualisation. A formal approach to framework development was taken, ensuring that resulting instrumentation systems are well specified. Both the framework development and its evaluation are linked to the full cycle of requirements setting, design, and deployment of a prototype instrumentation system for aerospace applicationsspecifically, health monitoring of a gas turbine engine. The FieldMAP (Field Monitoring Application Prototyping) framework supports multi-modal sensing, provides a number of opportunities for data processing and information extraction, caters for monitoring of the instrumentation health, offers a modular fieldmapping design component and allows for real-time phenomena visualisation, data and information logging and post-analysis. Experience with the FieldMAP has shown that sophisticated and robust prototypes can be developed in a short period of time.

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Section: Related Workmentioning

confidence: 99%

FieldMAP: A Spatiotemporal Field Monitoring Application Prototyping Framework

et al. 2009

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“…The system does not operate in real time, as the main purpose is collection of data to be fed to a simulator. A related system, described in [3], also uses a WSN to collect data for flood prediction, but carries out the computation locally, using a grid-based approach.…”

Section: Related Workmentioning

confidence: 99%

A Wireless System for Real-Time Environmental and Structural Monitoring

Plessi¹,

Bastianini

Sedigh³

2007

Software Technologies for Embedded and Ubiquitous Systems

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Abstract. Accurate real-time monitoring of structural health can result in significant safety improvements, while providing data that can be used to improve design and construction practices. For bridges, monitoring of water level, tilt, displacement, strain, and vibration can provide snapshots of the state of the structure. Real-time measurement and communication of this information can be invaluable in guiding decisions regarding the safety and remaining fatigue life of a bridge.This paper describes the real-time data acquisition, communication, and alerting capabilities of the Flood Frog, an autonomous wireless system for remote monitoring. Battery power and utilization of the GSM cellular network result in a completely wireless system. Coupled with the low cost of the device, the elimination of cables allows deployment in locations where autonomous monitoring is hindered by cost or infeasibility of installation. The first prototype of the system was deployed in Osage Beach, MO in November 2006.

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“…In other cases, however, as with the mobile computing scenarios mentioned above, parallel and distributed computation may also be carried out 'locally' using the nodes of the sensor network as a Grid or sub-Grid. An example of this from the research at Lancaster University is the use of networked sensor nodes to compute the flow rate of a river, based on an analysis of video images of the movement of flotsam on the river's surface [14]. This particular computation must be carried out locally because the sensor network's connectivity (GSM-based) to the wider Grid, although sufficient to carry other sensor data such as pressure and salinity, is insufficient to support the data rates necessary to ship raw video data offsite.…”

Section: A 'Possible Future' For the Gridmentioning

confidence: 99%